Cross-paradigm connectivity: reliability, stability, and utility.
Cross-paradigm connectivity: reliability, stability, and utility.
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DOI：
10.1007/s11682-020-00272-z
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发表时间：
2021-04
影响因子：
3.2
通讯作者：
Cannon TD
中科院分区：
文献类型：
--
作者：
Cao H;Chen OY;McEwen SC;Forsyth JK;Gee DG;Bearden CE;Addington J;Goodyear B;Cadenhead KS;Mirzakhanian H;Cornblatt BA;Carrión RE;Mathalon DH;McGlashan TH;Perkins DO;Belger A;Thermenos H;Tsuang MT;van Erp TGM;Walker EF;Hamann S;Anticevic A;Woods SW;Cannon TD
虽然功能性神经影像学研究通常集中在一个特定的范式来研究网络连接，但人类大脑似乎拥有一个独立于任何给定范式的内在“特质”架构。我们以前提出了使用“跨范式连接（CPC）”来量化跨多个范式的共享连接模式，并已证明了这些措施在临床研究中的实用性。在这里，使用概化理论和连接体指纹，我们研究了可靠性，稳定性，和个人识别CPC在一组高度采样的健康旅行受试者接受fMRI扫描与电池的五个范例在多个网站和天。与单范式连接矩阵相比，CPC矩阵在连接多样性方面具有更高的可靠性，在连接强度方面具有更低的可靠性，具有更高的稳定性和更高的个体识别准确性。所有这些评估都随着产品总分类分析所包括的范例数目的增加而增加。在涉及不同的范式组合和不同的大脑图谱的比较中，我们观察到显着更高的可靠性，稳定性和可识别性的CPC矩阵构建的任务只有数据（与那些从任务和休息数据），和较高的可识别性，但较低的稳定性CPC矩阵构建的功率图谱（与那些从AAL图谱）。此外，我们发现，多范式CPC矩阵可能反映了大脑的“特质”结构，即使多次运行，也无法从单范式数据中完全实现。本研究结果为CPC在功能性“特质”网络研究中的可行性和实用性提供了证据，并为今后CPC研究提供了一些方法学启示。
While functional neuroimaging studies typically focus on a particular paradigm to investigate network connectivity, the human brain appears to possess an intrinsic “trait” architecture that is independent of any given paradigm. We have previously proposed the use of “cross-paradigm connectivity (CPC)” to quantify shared connectivity patterns across multiple paradigms and have demonstrated the utility of such measures in clinical studies. Here, using generalizability theory and connectome fingerprinting, we examined the reliability, stability, and individual identifiability of CPC in a group of highly-sampled healthy traveling subjects who received fMRI scans with a battery of five paradigms across multiple sites and days. Compared with single-paradigm connectivity matrices, the CPC matrices showed higher reliability in connectivity diversity, lower reliability in connectivity strength, higher stability, and higher individual identification accuracy. All of these assessments increased as a function of number of paradigms included in the CPC analysis. In comparisons involving different paradigm combinations and different brain atlases, we observed significantly higher reliability, stability, and identifiability for CPC matrices constructed from task-only data (versus those from both task and rest data), and higher identifiability but lower stability for CPC matrices constructed from the Power atlas (versus those from the AAL atlas). Moreover, we showed that multi-paradigm CPC matrices likely reflect the brain’s “trait” structure that cannot be fully achieved from single-paradigm data, even with multiple runs. The present results provide evidence for the feasibility and utility of CPC in the study of functional “trait” networks and offer some methodological implications for future CPC studies.
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影响因子：
4.2
作者：
Hsu WT;Rosenberg MD;Scheinost D;Constable RT;Chun MM
通讯作者：
Chun MM
影响因子：
3.7
作者：
Cao, Hengyi;McEwen, Sarah C.;Cannon, Tyrone D.
通讯作者：
Cannon, Tyrone D.
DOI：
10.1146/annurev-clinpsy-040510-143934
发表时间：
2011-01-01
影响因子：
18.4
作者：
Bullmore, Edward T.;Bassett, Danielle S.
通讯作者：
Bassett, Danielle S.
影响因子：
5.7
作者：
Finn ES;Scheinost D;Finn DM;Shen X;Papademetris X;Constable RT
通讯作者：
Constable RT
DOI：
10.1177/1073858414525995
发表时间：
2014-12
期刊：
The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry
影响因子：
--
作者：
Cole MW;Repovš G;Anticevic A
通讯作者：
Anticevic A